Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.742187
Title: Modelling and simulation of heterogeneous growth dynamics in bacterial populations using a novel multiphasic growth method
Author: Du Lac, Melchior
ISNI:       0000 0004 7227 4449
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2017
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Abstract:
The cell cycle is an inevitable source of population heterogeneity, that creates predictable discontinuities. By summarising the canonical understanding of the major steps within the bacterial cell cycle into a mechanistic model, the Cooper-Helmstetter model is able to formally describe a number of population properties such as age, DNA and volume distributions. Although this model successfully describes many different attributes of a bacterial population, it is limited to exponential growth conditions. Outside of rigorous growth environments, bacterial populations contain innate temporal features that make them di cult to formalise theoretically using traditional mechanistic or equation based mathematical models. To model bacterial population cell cycle outside of exponential growth, the single cell cycle mechanistic model was inspected and expanded. A new individual based model was developed and a novel method to track the growth of a population using measured optical density data alone was developed. Together these new features made for the Heterogeneous Multiphasic Growth simulator, and were used to explore the chromosomal DNA dynamics of bacterial populations in disparate growth regimes. The effects of the recA1 mutation on the dynamics of the cell cycle was examined through optimisation to measured data. Furthermore, predictive modelling of theoretical effects of gene copy number and partition noise on synthetic genetic constructs expressed as ordinary differential equations were explored theoretically. By explicitly simulating each member of a population using such a method, a wide range of different aspects of bacterial population may be approached theoretically with more ease, and throughout more diverse growth dynamics.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.742187  DOI: Not available
Keywords: QH301 Biology
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